Maximum Entropy Dreamer uses the same hyperparameters and coefficients as a Revised Dreamer except that it is no longer uses additive random noise for exploration. For MDN, we set the hidden size to 256, a number of heads to 8, the coefficient of soft update of target MDN to \(0.1\) , and the discount factor for discounted state distribution to \(0.9\) . The MDN were trained with a learning rate \(0.0002\)  with Adam optimizer [1]}. An entropy coefficient \(\beta \)  in actor optimization objective (equation REF ) is linearly decreasing from \(0.2\)  to \(0.0001\)  during the training process.
